What are the hardware requirements for Leniachat Gemma 2B V0?

Leniachat Gemma 2B V0 requires approximately 15.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Leniachat Gemma 2B V0 and how large is it?

Leniachat Gemma 2B V0 is developed by LenguajeNaturalAI, a model with 2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Leniachat Gemma 2B V0?

Leniachat Gemma 2B V0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Leniachat Gemma 2B V0 by LenguajeNaturalAI — VRAM 15.1GB, 8K context

Name: Leniachat Gemma 2B V0
Author: LenguajeNaturalAI

Leniachat Gemma 2B V0 is an open-source language model by LenguajeNaturalAI. Features: 2b LLM, VRAM: 15.1GB, Context: 8K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.13.

Base model:finetune:google/gem... Base model:google/gemma-2b Chat Conversational Endpoints compatible Es Gemma Instruct Multi-task-learning Qa Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LenguajeNaturalAI/leniachat-gemma-2b-v0

Leniachat Gemma 2B V0 Parameters and Internals

Model Type

text-generation-inference, transformers, chat, qa, multi-task-learning, instruction-tuning

Use Cases

Applications:

text generation, chatbots, virtual assistants

Limitations:

Limited to Spanish language, Biases and errors possible due to model size

Considerations:

Evaluate performance in specific context and use responsibly

Additional Notes

Model has limitations inherent to 2 billion parameter base size

Supported Languages

es (high proficiency)

Training Details

Methodology:

Three-phase training: multi-task learning, high-quality instruction tuning, chat and QA training

Context Length:

8192

Input Output

Performance Tips:

Consider hardware capabilities due to model size

LLM Name	Leniachat Gemma 2B V0
Repository 🤗	https://huggingface.co/LenguajeNaturalAI/leniachat-gemma-2b-v0
Base Model(s)	Gemma 2B google/gemma-2b
Model Size	2b
Required VRAM	15.1 GB
Updated	2026-06-26
Maintainer	LenguajeNaturalAI
Model Type	gemma
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 4.9 GB: 1-of-3 0.1 GB: 2-of-2 5.0 GB: 2-of-3 0.1 GB: 3-of-3
Supported Languages	es
Model Architecture	GemmaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.38.2
Tokenizer Class	GemmaTokenizer
Padding Token	[PAD]
Vocabulary Size	256008
Torch Data Type	bfloat16

Rank the Leniachat Gemma 2B V0 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Gita SastraGPT V1	8K / 5.1 GB	4	1
Pandas Tutor Gemma 2B	8K / 5.1 GB	6	1
... 2B Finetuned Sft Navarasa 2.0	8K / 10 GB	536	27
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Gemma 2B Sft Preview	8K / 5 GB	13	0
...ma Instruct Finetune On Alpaca	8K / 5.1 GB	5	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	10	0
Gemma 2B Persona Instruct	8K / 5.1 GB	5	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	6	0
...ma Code Instruct Finetune Test	8K / 5.1 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than LenguajeNaturalAI/leniachat-gemma-2b-v0.